This invention relates generally to autonomous control systems for vehicles, and more particularly to autonomous control systems for vehicles using sensors.
Autonomous control systems are systems that guide vehicles (e.g., automobiles, trucks, vans) without direct guidance by human operators. Autonomous control systems analyze the surrounding physical environment in various ways to guide vehicles in a safe manner. For example, an autonomous control system may detect and/or track objects in the physical environment, and responsive to a detected object, guide the vehicle away from the object such that collision with the object can be avoided. As another example, an autonomous control system may detect boundaries of lanes on the road such that the vehicle can be guided within the appropriate lane with the flow of traffic.
Often times, autonomous control systems use computer models to perform algorithms for analyzing the surrounding environment and performing detection and control operations. The computer models are trained from data sets containing information that resemble potential environments the autonomous control system would encounter during operation. For example, a computer model for detecting pedestrians on the street may learn different representations of people from a data set containing various images of pedestrians. Typically, the performance of computer models improves with the amount of data available for learning. However, gathering data for training computer models is often costly and time-consuming.